Triple

T5909367
Position Surface form Disambiguated ID Type / Status
Subject University of Lagos E131421 entity
Predicate otherCampusLocation P116 FINISHED
Object Yaba, Lagos E288160 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Yaba, Lagos | Statement: [University of Lagos, otherCampusLocation, Yaba, Lagos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yaba, Lagos
Context triple: [University of Lagos, otherCampusLocation, Yaba, Lagos]
  • A. Ikoyi
    Ikoyi is an affluent, high-end residential and commercial district in Lagos, Nigeria, known for its luxury real estate, upscale hotels, and diplomatic presence.
  • B. Lagos Mainland
    Lagos Mainland is a densely populated urban area of Lagos, Nigeria, known for its residential neighborhoods, commercial hubs, and vibrant cultural life distinct from the more upscale Lagos Island.
  • C. Ibadan
    Ibadan is one of the largest and most populous cities in southwestern Nigeria, historically significant as a major Yoruba cultural and economic center.
  • D. Ilorin
    Ilorin is a major city in western Nigeria and the capital of Kwara State, known as a historic Yoruba and Islamic cultural center.
  • E. Yaba chosen
    Yaba is a bustling commercial and residential district on Lagos Mainland in Nigeria, known for its markets, educational institutions, and growing tech startup scene.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c008593a44819081a07ae0efe6c574 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03775590481909a797b166fbe108c completed March 22, 2026, 6:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0c015b90081909777ac5ed80e927c completed March 23, 2026, 4:22 a.m.
Created at: March 22, 2026, 3:59 p.m.